chore(pyamber): interpolate the offending type in the BATCH_SIZE validation error

amber/src/main/python/core/models/operator.py

@@ -206,7 +206,7 @@ def _validate_batch_size(value):
         if value is None:
             raise ValueError("BATCH_SIZE cannot be None.")
         if type(value) is not int:
-            raise ValueError("BATCH_SIZE cannot be {type(value))}.")
+            raise ValueError(f"BATCH_SIZE cannot be {type(value)}.")
         if value <= 0:
             raise ValueError("BATCH_SIZE should be positive.")
 

amber/src/test/python/core/models/test_operator.py

@@ -208,6 +208,28 @@ def test_validate_batch_size_rejects_non_int(self):
         with pytest.raises(ValueError):
             BatchOperator._validate_batch_size("10")
 
+    def test_validate_batch_size_non_int_message_names_the_float_type(self):
+        # The message must name the offending type, not a template literal.
+        with pytest.raises(ValueError) as excinfo:
+            BatchOperator._validate_batch_size(10.0)
+        assert str(excinfo.value) == "BATCH_SIZE cannot be <class 'float'>."
+
+    def test_validate_batch_size_non_int_message_names_the_str_type(self):
+        with pytest.raises(ValueError) as excinfo:
+            BatchOperator._validate_batch_size("10")
+        assert str(excinfo.value) == "BATCH_SIZE cannot be <class 'str'>."
+
+    def test_concrete_batch_operator_with_float_size_reports_type_in_message(self):
+        class _FloatBatch(BatchOperator):
+            BATCH_SIZE = 10.0
+
+            def process_batch(self, batch, port):
+                yield batch
+
+        with pytest.raises(ValueError) as excinfo:
+            _FloatBatch()
+        assert str(excinfo.value) == "BATCH_SIZE cannot be <class 'float'>."
+
     def test_validate_batch_size_rejects_zero(self):
         with pytest.raises(ValueError, match="positive"):
             BatchOperator._validate_batch_size(0)